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Data Migration Manager Jobs in California (NOW HIRING)

Scalence L.L.C.

Veeva Solution Architect

Cupertino, CA · On-site

$77.75 - $102.50/hr

The role involves leading architecture and data migration strategies while collaborating with cross ... able to manage pressure. • Attention to detail. • The ability to work in a team and ...

Keylent Inc

Team Center Architect MAHIN-JOB-32897

Fremont, CA · On-site

$69.25 - $91.25/hr

The role involves end-to-end implementation and data migration of Teamcenter solutions for semiconductor clients. Responsibilities : • Team Center Solution Architect/Product Manager with minimum 15 ...

CYNET SYSTEMS

Senior Data Engineer

San Jose, CA · On-site

$55 - $60/hr

... scale data migration projects. * Strong to expert-level proficiency in Python for building and ... Proven experience designing and managing ETL/ELT pipelines at scale (millions of records)

CYNET SYSTEMS

Data Tech Lead with Java

Aliso Viejo, CA · On-site

$61 - $66/hr

... management of Databricks notebooks, jobs, and data pipelines. * Support Snowflake on-premises to Azure cloud migration initiatives. * Ensure coding standards, performance tuning, monitoring, and ...

Laiba Technologies LLC

Data Engineer

San Jose, CA · On-site

$134K - $161K/yr

... scale data migration projects Strong to expert-level proficiency in Python for building and ... managing ETL/ELT pipelines at scale (millions of records) Experience mapping and transforming ...

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Showing results 41-60

All JobsData Migration JobsData Migration Manager JobsData Migration Manager Jobs in California

Data Migration Manager information

See California salary details

$30.6K

$95.9K

$169.7K

How much do data migration manager jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data migration manager in California is $95,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,100.00 and $123,900.00 per year, depending on experience, location, and employer.

What is a data migration manager?

A Data Migration Manager is a professional responsible for planning, coordinating, and overseeing the transfer of data between storage systems, databases, or formats, typically during system upgrades or consolidations. They ensure that data is accurately and securely moved with minimal disruption to business operations. Their role involves developing migration strategies, managing risks, addressing data integrity issues, and collaborating with IT teams and stakeholders throughout the process.

What are the key skills and qualifications needed to thrive as a data migration manager?

To thrive as a Data Migration Manager, you need expertise in data management, project management, and a deep understanding of database systems, often supported by a degree in computer science or information technology. Familiarity with ETL tools, data mapping software, cloud platforms, and certifications such as PMP or Microsoft Azure Data Engineer are highly valuable. Strong problem-solving, communication, and leadership skills help in coordinating teams and ensuring clear stakeholder engagement. These capabilities are essential for delivering seamless, secure, and timely data migrations that minimize risk and business disruption.

What are some common challenges faced by data migration managers during large-scale system transitions?

Data Migration Managers often encounter challenges such as data quality issues, mismatched data formats, and tight project timelines during large-scale system transitions. Coordinating across multiple departments to ensure data integrity and minimize downtime requires strong communication and project management skills. Additionally, adapting to unexpected technical issues or legacy system constraints is common, making proactive planning and risk mitigation essential to a successful migration.

What is the difference between Data Migration Manager vs Data Analyst?

AspectData Migration ManagerData Analyst
Required CredentialsBachelor's in IT, Computer Science, or related; certifications like PMP or data management certificationsBachelor's in Statistics, Mathematics, or related; often certifications in data analysis tools
Work EnvironmentProject-based, IT departments, data migration projectsBusiness units, analytics teams, reporting environments
Employer & Industry UsageIT firms, large corporations, data integration projectsMarketing, finance, healthcare, and other sectors analyzing data
Common Search & ComparisonOften compared for project management and technical skillsCompared for data interpretation and reporting skills

The Data Migration Manager focuses on planning and executing data transfer projects, ensuring data integrity and system compatibility. In contrast, a Data Analyst interprets data to provide insights and support decision-making. While both roles work with data, their core responsibilities and skill sets differ significantly.

What are the most commonly searched types of Data Migration jobs in California?

The most popular types of Data Migration jobs in California are:

What are popular job titles related to Data Migration Manager jobs in California?

For Data Migration Manager jobs in California, the most frequently searched job titles are:

What job categories do people searching Data Migration Manager jobs in California look for?

The top searched job categories for Data Migration Manager jobs in California are:

What cities in California are hiring for Data Migration Manager jobs?

Cities in California with the most Data Migration Manager job openings:

Data Migration Manager jobs near you
Infographic showing various Data Migration Manager job openings in California as of August 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $95,873 per year, or $46.1 per hour.

Sr. Data Engineer, Mircosoft Fabric

Lobel Financial Corporation

Anaheim, CA • On-site

$119K - $143K/yr

Full-time

Posted 14 days ago

Job description

We are seeking a Senior Data Engineer with hands-on Microsoft Fabric experience to design, build, migrate, and support enterprise data platforms. This role develops scalable ETL and ELT pipelines, implements Medallion Architecture in OneLake, Lakehouse, and Fabric Warehouse, and delivers reliable data for analytics and Power BI. The engineer partners with architects, application teams, analysts, BI developers, infrastructure teams, and business stakeholders to implement secure, governed, and high-performing data solutions.


Core Skills

Microsoft Fabric architecture and engineering: Microsoft Fabric, Data Factory, Data Pipelines, Dataflows Gen2, OneLake, Lakehouse, Fabric Warehouse, Notebooks, and Medallion Architecture.

Data pipeline development and programming: ETL/ELT, SQL, T-SQL, Python, PySpark, Spark, batch processing, incremental processing, change data capture (CDC), upsert/merge strategies, and metadata-driven frameworks.

Data migration, warehousing, and modeling: legacy platform migration, source-to-target mapping, data profiling, cleansing, reconciliation, validation, dimensional modeling, star schemas, fact tables, dimension tables, and slowly changing dimensions.


Key Responsibilities

Design, develop, test, deploy, and maintain scalable end-to-end data pipelines for batch, incremental, and near-real-time processing.

Build data ingestion and transformation solutions using Microsoft Fabric Data Factory, Data Pipelines, Dataflows Gen2, Notebooks, SQL, Python, PySpark, Spark, and T-SQL.

Develop reusable, metadata-driven ETL/ELT frameworks that support relational databases, APIs, files, SaaS applications, cloud platforms, and structured or semi-structured data.

Implement CDC, incremental loads, upsert/merge patterns, historical processing, error handling, monitoring, and data-quality controls.

Lead legacy-to-modern data migrations, including data profiling, source-to-target mapping, cleansing, transformation, reconciliation, validation, and cutover support.

Design and implement Medallion Architecture using OneLake, Fabric Lakehouse, and Fabric Warehouse.

Create enterprise data warehouse models using dimensional modeling, star schemas, fact tables, dimension tables, and slowly changing dimensions.

Troubleshoot pipeline, data, integration, and performance issues and optimize Microsoft Fabric workloads and capacity utilization.

Document data flows, mappings, standards, lineage, and operating procedures.

Collaborate with technical and business stakeholders to deliver secure, governed, reliable, and scalable data solutions.


Required Qualifications

5+ years of professional experience in data engineering, data integration, data warehousing, business intelligence, or a related field.

Hands-on experience implementing Microsoft Fabric in a production or enterprise environment.

Experience with Microsoft Fabric Data Factory, Data Pipelines, Dataflows Gen2, OneLake, Lakehouse, Fabric Warehouse, and Notebooks.

Experience designing and implementing Medallion Architecture and enterprise ETL/ELT solutions.

Strong SQL and T-SQL development skills.

Strong Python and/or PySpark experience for data engineering and transformation.

Experience with Spark-based batch and incremental data processing.

Experience with legacy-to-modern data migration, data profiling, source-to-target mapping, transformation, reconciliation, and validation.

Strong knowledge of data warehousing and dimensional modeling, including star schemas, fact tables, dimension tables, and slowly changing dimensions.

Experience with data quality, monitoring, error handling, troubleshooting, and performance optimization.

Strong analytical, problem-solving, written communication, verbal communication, and documentation skills.


Preferred Qualifications

Microsoft Certified: Fabric Data Engineer Associate or another relevant Microsoft certification.

Experience with Power BI, semantic models, Direct Lake, DAX, and enterprise reporting.

Experience with Delta Lake, Snowflake, SQL Server, Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, or Azure Databricks.

Experience integrating APIs and REST services and working with JSON, XML, or other semi-structured data.

Experience with streaming or near-real-time data integration.

Experience with enterprise data governance, metadata management, data lineage, cataloging, and automated data-quality testing.

Experience supporting large-scale modernization or data migration programs.

Experience working in Agile or Scrum environments.

Experience mentoring data engineers and establishing engineering standards.

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